Yonger Zuo
Papers
1
Total Citations
5
H-Index
1
About
Yonger Zuo is a leading researcher in human-robot interaction (HRI) safety, whose work systematically uncovers the hidden patterns behind robot-related accidents. By analyzing 303 accident reports, Zuo identified seven distinct HRI incident archetypes, revealing that unexpected activation and sensor errors are the dominant failure modes across different stages of robotic technology deployment. This foundational study, which has already garnered 5 citations since its 2025 publication, applies systems thinking to demonstrate how complex interactions between robot design flaws, human error, and environmental hazards converge to produce critical incidents. Zuo’s major contribution lies in moving beyond isolated case studies to provide a network-level understanding of HRI accidents, offering engineers and policymakers a structured framework for anticipating and mitigating risks before they escalate. This work positions Zuo as a key voice in the growing field of safe human-robot collaboration, where their archetype taxonomy serves as both a diagnostic tool and a design guide for next-generation autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1